- About this Journal
- Abstracting and Indexing
- Aims and Scope
- Article Processing Charges
- Articles in Press
- Author Guidelines
- Bibliographic Information
- Citations to this Journal
- Contact Information
- Editorial Board
- Editorial Workflow
- Free eTOC Alerts
- Publication Ethics
- Reviewers Acknowledgment
- Submit a Manuscript
- Subscription Information
- Table of Contents
Advances in Numerical Analysis
Volume 2012 (2012), Article ID 912810, 10 pages
doi:10.1155/2012/912810
Approximation Solution of Fractional Partial Differential Equations by Neural Networks
Department of Mathematics, Faculty of Education, Thamar University, Thamar, Yemen
Received 1 October 2011; Accepted 21 November 2011
Academic Editor: Muhammed I. Syam
Copyright © 2012 Adel A. S. Almarashi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Neural networks with radial basis functions method are used to solve a class of initial boundary value of fractional partial differential equations with variable coefficients on a finite domain. It takes the case where a left-handed or right-handed fractional spatial derivative may be present in the partial differential equations. Convergence of this method will be discussed in the paper. A numerical example using neural networks RBF method for a two-sided fractional PDE also will be presented and compared with other methods.